A new model of electromechanical relays for predicting the motion and electromagnetic dynamics

In this paper, a novel multiphysics and nonlinear model for electromechanical relays is presented. The electromagnetic dynamics is analyzed by calculating the total reluctance of the magnetic equivalent circuit (MEC), which is composed of a fixed length iron core and an angular air gap. Magnetic saturation and angular dependency of the reluctance are considered in the analysis. Then, an energy balance over the electromagnetic components of the system is used to obtain the torque which drives the movable armature. A planar mechanism of four rigid bodies, including spring-damping torques that restrict the motion and model the contact bounces that occur in the switchings, is proposed to explain the dynamics of the movable components. Experimental tests show the accuracy of the model in both the electromagnetic and the mechanical parts

Model-free sliding-mode controller for soft landing of reluctance actuators

Some electromagnetic actuators suffer from high velocity impacts during non-controlled switching operations, which cause contact bouncing, mechanical wear, and acoustic noise. Soft-landing control strategies aim at minimizing the impact velocities of these devices to improve their performance. This paper presents a sliding-mode controller for soft landing of single-coil reluctance actuators. It is a switching model-free controller, which results in a very simple implementation. A generalized dynamical hybrid model of an actuator is utilized for deriving the robustness condition, based on the Lyapunov theory. Then, the condition is evaluated for a dynamical model, based on a commercial device, and several reference trajectories. Finally, the controller performance is validated through simulations. The effect of the sampling rate on the resulting impact velocities is also analyzed

Design of a perfect-tracking soft-landing controller for electromagnetic switching devices

Electromagnetic switching devices such as electromechanical relays and solenoid valves suffer from impacts and mechanical wear when they are activated using a constant-voltage policy. This paper presents a new control approach that aims at achieving soft landing in these devices, i.e., a movement without neither impacts nor bouncing. The hybrid nonlinear dynamics of the system is firstly described taking into account the limited range of motion that characterizes this class of devices. Then, the nonlinear expression of the control law is derived and a method to design a soft-landing reference trajectory is proposed. It is shown that, when certain conditions are met, the design methodology presented in the paper results in a controller that achieves perfect tracking of the reference trajectory and, hence, soft landing is accomplished. The theoretical analysis is validated by simulation using a dynamical model of a specific switching device

Hybrid dynamical model for reluctance actuators including saturation, hysteresis and eddy currents

A novel hybrid dynamical model for single-coil, short-stroke reluctance actuators is presented in this paper. The model, which is partially based on the principles of magnetic equivalent circuits, includes the magnetic phenomena of hysteresis and saturation by means of the generalized Preisach model. In addition, the eddy currents induced in the iron core are also considered, and the flux fringing effect in the air is incorporated by using results from finite element simulations. An explicit solution of the dynamics without need of inverting the Preisach model is derived, and the hybrid automaton that results from combining the electromagnetic and motion equations is presented and discussed. Finally, an identification method to determine the model parameters is proposed and experimentally illustrated on a real actuator. The results are presented and the advantages of our modeling method are emphasized

Probability-Based Optimal Control Design for Soft Landing of Short-Stroke Actuators

The impact forces during switching operations of short-stroke actuators may cause bouncing, audible noise, and mechanical wear. The application of soft-landing control strategies to these devices aims at minimizing the impact velocities of their moving components to ultimately improve their lifetime and performance. In this brief, a novel approach for soft-landing trajectory planning, including probability functions, is proposed for optimal control of the actuators. The main contribution of the proposal is that it considers the uncertainty in the contact position, and hence, the obtained trajectories are more robust against system uncertainties. The problem is formulated as an optimal control problem and transformed into a two-point boundary value problem for its numerical resolution. Simulated and experimental tests have been performed using a dynamic model and a commercial short-stroke solenoid valve. The results show a significant improvement in the expected velocities and accelerations at contact with respect to past solutions in which the contact position is assumed to be perfectly known

Run-to-run adaptive nonlinear feedforward control of electromechanical switching devices

Feedforward control can greatly improve the response time and control accuracy of any mechatronic system. However, in order to compensate for the effects of modeling errors or disturbances, it is imperative that this type of control works in conjunction with some form of feedback. In this paper, we present a new adaptive feedforward control scheme for electromechanical systems in which real-time measurements or estimates of the position and its derivatives are not technically or economically feasible. This is the case, for example, of commercial electromechanical switching devices such as solenoid actuators. Our proposal consists of two blocks: on the one hand, a feedforward controller based on differential flatness theory; on the other, an iterative adaptation law that exploits the repetitive operation of these devices to modify the controller parameters cycle by cycle. As shown, this law can be fed with any available measurement of the system, with the only requirement that it can be processed and converted into an indicator of the performance of any given operation. Simulated and experimental results show that our proposal is effective in dealing with a long-standing control problem in electromechanics: the soft-landing control of electromechanical switching devices

Nonlinear Bounded State Estimation for Sensorless Control of an Electromagnetic Device

This paper presents a novel nonlinear state observer with discrete-time measurements for estimating the plunger position of linear travel solenoid valves. The observer is an unscented Kalman filter (UKF) for nonlinear systems that iteratively calculates an estimated mean and covariance of the state. It is based on a basic lumped parameter model, which contributes to the computational efficiency of the observer and facilitates its implementation. The magnetic reluctance is modeled taking into account the magnetic saturation and is partly defined by data obtained from finite element analysis (FEA). Boundary constraints are added to the estimated position to prevent it from surpassing its physical limits. Different tests performed with simulated and experimental data show that the estimations are accurate and robust to noise and model inaccuracies. Besides, although the observer has been developed for a specific device, the method can be easily extended to other electromechanical systems in which the position needs to be estimated

On the Stability of Electromechanical Switching Devices: A Study of Hysteretic Switching Behaviors

Electromagnetic relays and solenoid actuators are commercial devices that generally exhibit bistable behavior. In fact, this is the reason why they are extensively used to switch between two possible configurations in electrical, pneumatic, or hydraulic circuits, among others. Although the state of the art is extensive on modeling, estimation, and control of these electromechanical systems, there are very few works that focus on analysis aspects. In this paper, we present an equilibrium and stability analysis whose main goal is to provide insight into such bistable behavior. The study is based on a hybrid dynamical model of the system also presented in the paper. This model is used to obtain analytic expressions that relate the physical parameters to the switching conditions. The results are extensively discussed and possible practical applications are also proposed. Finally, experimental results with a real device are used for validation of the theoretical analysis and also for illustrating one of the possible practical uses

ROM-Based Stochastic Optimization for a Continuous Manufacturing Process

This paper proposes a model-based optimization method for the production of automotive seals in an extrusion process. The high production throughput, coupled with quality constraints and the inherent uncertainty of the process, encourages the search for operating conditions that minimize nonconformities. The main uncertainties arise from the process variability and from the raw material itself. The proposed method, based on Bayesian optimization, takes these factors into account and obtains a robust set of process parameters. Due to the high computational cost and complexity of performing detailed simulations, a reduced order model is used to address the optimization. The proposal has been evaluated in a virtual environment where it is shown that the performance of the solution found minimizes the effects of process uncertainties.Comment: 7 pages, 8 figure

Thermal modeling, analysis and control using an electrical analogy

Modeling and identification of thermal systems is a problem frequently treated in theoretical and application domains. Most of these systems have been modeled using black-box structures whose parameters are identified using temperature measurements. Although black-box models have achieved good results in terms of temperature evolution, they cannot model variables which had not been measured in the identification test. In this article we present a new method to build grey-box thermal models based on electrical equivalent circuits which not only give information about temperatures evolution, but also about heat fluxes and thermal energy stored in the system. The partially unknown parameters of the models are identified using temperature measurements and applying nonlinear optimization techniques. The obtained state space representation can be used to develop a deterministic state space temperature controller that provides better accuracy than classical PID controllers. Our proposal is complemented with various examples of a real application in an electric oven